A Comparison of Ground Source Heat Pumps
and Micro-Combined Heat and Power
as Residential Greenhouse Gas Reduction Strategies
by
Brittany Guyer
Submitted to the Department of Mechanical Engineering in Partial
Fulfillment of the Requirements for the
Degree of
MASSACHUSETTS INSTTUTE
OF TECHNOLOGY
Bachelor of Science
SEP 1 6 2009
at the
L ,R
Massachusetts Institute of Technology
RIS
ARCHIVES
3une 2009
© 2009 Brittany Guyer
All rights reserved
The author hereby grants to MIT permission to reproduce and to
paper and electronic copies of this thesis document in whole or in part
publicly
distribute
in any medium now known or hereafter created.
....
.............................. ...... . ....
S ignature of A uthor ...
...........
. ................... ...
Departm
..
tof Mechanical Engineering
May 11, 2009
Certified by ........................................
Professor Ernest G. Cravalho
Professor of Mechanical Engineering
Van Buren N. Hansford Faculty Fellow
Thesis Supervisor
Accepted by ...................
...............
..........
..
.......
Professor J. Lienhard V
essor of Mechanical Engineering
Chairman, Undergraduate Thesis Committee
Table of Contents
Abstract
Page 3
1. Literature Review
1.1 Ground Source Heat Pumps
1.2 Micro-Combined Heat and Power (Micro-CHP)
3
3
4
2. Electric Power Data Collection
5
3. Conventional Home Energy Systems
7
4. Ground Source Heat Pump Model
8
5. Micro-CHP Model
11
6. House Model
13
7. Carbon Comparison Calculations
7.1 Carbon Produced by Conventional Home
7.2 Carbon Produced by GSHP Home
7.3 Carbon Produced by Micro-CHP Home
7.4 Electric Grid Carbon Characteristic: Impact on Analysis
15
15
16
16
17
8. Results and Conclusions
8.1 Results Using Average CO 2 Emissions Rate for Local
Grid Electricity
8.2 Results Using Fossil Fuel Generation CO 2 Emissions Rate
For Local Grid Electricity
19
20
References
27
Appendix A: Micro-CHP and GSHP Annual CO 2 Emission Comparison
by State
29
Appendix B: Table of CO 2 Emissions by City for Grid Average and Fossil
Fuel Plant Emission Rates
40
Appendix C: Micro-CHP Total Carbon Profile Data
41
Appendix D: GSHP Total Carbon Profile Data
42
Appendix E: Conventional System Total Carbon Profile Data
43
Appendix F: State Average Carbon Profile Data
44
24
Abstract
Both ground source heat pumps operating on electricity and micro-combined heat and
power systems operating on fossil fuels offer potential for the reduction of green house gas
emissions in comparison to the conventional approaches for providing heating, air conditioning
and electric power to residential homes. Factors that may impact the relative merits are actual
system operating efficiencies, regional primary energy sources for electric power generation,
actual space conditioning and electric demands as well as regional climate factors. The purpose
of this study is to make a consistent, realistic comparison of these greenhouse gas reduction
strategies as applied to typical single-family residential homes across the United States. The
study identifies both the regional variations and specific magnitudes of reductions that could be
expected with these technologies when implemented within the current energy infrastructure.
These comparisons are achieved by identifying the performance characteristics of both
technologies, developing typical application scenarios and collecting important regional data
associated with electric power production and climate variations. The results show that indeed
regional variations exist in the relative merits of micro-CHP systems and ground source heat
pumps on reducing the carbon emissions for households.
Specific results are sensitive to the
assumptions made regarding the carbon production characteristics of incremental increases or
decreases of electrical demand on the local electricity utility grid.
1. Literature Review
1.1 Ground Source Heat Pumps
Ground source heat pumps are a readily available commercial technology. Currently the
world leaders in ground source heat pump (GSHP) installations are the USA, Sweden, Germany,
Canada and Switzerland. Installations are available in a variety of forms, mostly dependent upon
the terrain surrounding the site of application. Lund et al. [1] summarized the various options for
GSHP installation as well as the technology's current status in the countries in which it is most
frequently installed. With regard to the environmental impact of GSHP technology, Lund et al.
argue for increased production of renewable electricity on the electric grid as this would make
GSHP 100% renewable. They calculate the amount of less carbon produced by not using fossil
fuels to heat homes, but do not make any attempt to address the carbon production that results
from the production of grid electricity.
Hanova et al. [2] focuses on the specific applications for which net carbon emissions will
be reduced when comparing the conventional home heating methods: gas, oil and electric, to the
emissions generated by the central power plant associated with the amount of electricity needed
to run the GSHP. Economic analysis of GSHP is performed by examining average fuel and
electric prices in various countries to determine economic payback of the system. Finally, scale
effects of GSHP are examined to determine the manner in which GHG reduction and annual
economic savings are associated with heat load. The accompanying equations serve as a good
reference for the basic savings and emissions calculations. Although Hanova et al. address the
issue of net emissions associated with GSHP, they do not go so far as to identify any regional
trends arising from varying primary energy sources. Instead, they simply sets guidelines for
implementation based upon average cost and emissions data.
The Energy Center of Wisconsin [3] looked specifically at various sized GSHP
installations in Wisconsin and determined the reduction of GHG emissions associated with each
type of installation by examining the primary fuel associated with power generation in three
areas of the state. The results showed that emission reductions were achieved for large sized
applications: offices and schools, but for residential applications where GSHP were used to
replace conventional gas heating, there was actually an increased amount of GHG emissions
associated with the GSHP installations due to the source of grid electricity largely being coal.
The report also examined the economics of GSHP and showed that there was total resource
energy savings associated with all classifications of installations as well as achievable payback
in 10 - 25 years depending upon the sizing of the application.
1.2 Micro-Combined Heat and Power (Micro-CHP)
Unlike ground source heat pumps, micro-CHP systems have been created using a variety
of technologies.
Currently, systems to date include those based upon reciprocating internal
combustion engines, micro turbines, Stirling engines and fuel cells. Although systems exist
incorporating all of these technologies, there do no exist market ready technologies in every
category.
Onovwiona et al. [4] surveys the current existing technologies that have potential to serve
as options in the residential market. Systems incorporating reciprocating internal combustion
engines range in size from 1kW to 10MW electric and can be operated using a variety of fuels
making them applicable to a variety of residential situations. The efficiency of cogeneration
systems using reciprocating internal combustion engines ranges from 85-90%.
Micro-turbine based cogeneration systems range in size from 25-80 kW and achieve
operating efficiencies of 80%. Compared to reciprocating internal combustion engines, microturbines typically have a smaller relative size and fewer moving parts leading to less demand for
maintenance. Like reciprocating internal combustion engines, micro-turbines also have the
ability to operate on a variety of fuels. These systems may be appropriate for cogeneration
systems serving house communities, but are much too large for individual residences.
Fuel cell micro cogeneration systems' greatest attraction is their low emissions profile
and low noise levels; however, they are still very expensive and have not yet demonstrated long
lifetime. They operate at system efficiencies of up to 80% and due to their low number of
moving parts, offer the potential for relatively low maintenance costs.
Micro-CHP systems based on Stirling engines are not widely implemented; however,
they are currently under active development.
Because the heat supply to these engines is
external they offer the possibility for using a variety of primary fuels as well as reduced
maintenance. Efficiencies of Stirling micro-CHP systems range from 65%-85% with electrical
outputs of 1 kW to IMW.
As a means for the reduction of GHG emissions, micro-CHP has been shown to be a
universally effective technology by Pehnt et al. and Peacock et al. [5,6]; however, to date there
have been no known US regional comparisons conducted concerning the GHG reduction
potential of GSHP versus micro-CHP.
2. Electric Power Data Collection
Since the aim of this study is to determine the regional differences associated with the
carbon production resulting from the implementation of GSHP and Micro-CHP, regional electric
power emissions data was collected for 100 major cities in the United States. This information
facilitates assessment of the carbon production impact of the increasing electric demand on the
grid, due to ground source heat pump systems and the decreasing demand on the grid resulting
from the use of micro-combined heat and power systems. City selection was done in three
stages.
First, the most populous city from each state was selected.
Second, the 50 most
populous cities in the country were selected. Naturally, there was some overlap between these
two categories. The remaining cities were chosen based upon population rank within individual
states as well as geographical location. So, for instance, if the second largest city was very close
in proximity to the largest city within a particular state, and the third largest city was located on
the other side of the state, the third largest would be selected over the second largest. Having a
wider variety of geographical locations allows for a more accurate description of the
geographical variations resulting from the implementations of the technologies.
In order to determine the amount of carbon produced at central power stations per unit of
electricity, data from the EPA was used.
The EPA provides online accessible models that
calculate the carbon emissions from electric power plants for cities across the United States [7].
The data input is in the form of a zip code and the output emission rate of CO 2 is given in
lbs/MWh of produced power. The model calculates the CO 2 emission rates based upon the fuel
source and corresponding plant efficiencies of the power plants in a specific region. To use the
model, appropriate zip codes were collected for each city and input into the model to determine
the regional CO 2 output emission rate. This model provides the local grid average for carbon
emissions resulting from electric power production.
Use of the local grid average for carbon emissions has been questioned as being
appropriate for determining the marginal carbon production impacts of electric conservation or
electric-using technologies. The reason for this is that the total electric power demand on the
grid varies daily.
Therefore, the types of power generation, and their associated carbon
production characteristics, used to meet incremental loads at any one time on the grid, are likely
to be different from the grid average and relative carbon production average.
For example,
nuclear plants are carbon free and run continuously, while much of the "peaking" capacity of the
grid is fossil fuel based. Some experts in the field of energy analysis have suggested that use of
the local grid average fossil fuel plant carbon emission rates is the most appropriate
characteristic to use when analyzing technologies that have associated incremental electrical
loads (or reductions) since this more closely represents the actual change exhibited in grid power
plant usage. Appendix B provides the data for these two different assumptions.
3. Conventional Home Energy Systems
In order to provide an appropriate context for the study of ground source heat pumps and
micro-CHP, the conventional means for heating and cooling a home will be discussed.
In the United States, the most common means for heating a home is through the use of a
warm-air furnace which uses natural gas as a fuel. For the single-family detached housing unit,
which will serve as the model home type in this study, 46% use natural gas warm-air furnaces
[8]. The operation of a natural gas warm-air furnace is rather simple. Natural gas is taken from
the pipeline and combusted. Through means of a heat exchanger, the heat of combustion is then
transferred to the circulating air, which is then driven around the house by a fan.
In order to make the comparison of a warm-air natural gas furnace to the implementation
of a ground source heat pump and micro-CHP, the furnace used for comparison will be one of
the high efficiency class. High efficiency furnaces can achieve efficiencies up to 97%. The
efficiency of the furnace represents the total BTU heat output over the total BTU fuel input (eqn.
1).
BTUheat output
]'furnace
BTU
BTUfuel input
Since the thermal efficiency characterizes the operation of the whole system, a specific model
need not be chosen. For the purposes of this study an efficiency of 95% will be used as it
represents the operation of a furnace likely to be found in a high efficiency home.
Since the objective of this study is to determine a home's annual environmental impact, a
conventional cooling system was selected to serve as the cooling component for a conventional
home as well as a home which uses micro-CHP for heating. A conventional cooling system is
not needed in the home with a ground source heat pump as the ground source heat pump
provides cooling for the home in the summer.
Cooling systems are characterized by an efficiency known as the energy efficiency ratio,
or EER. This ratio represents the BTU of output cooling over the kilowatt-hour of electricity
input (eqn. 2); therefore the higher the EER, the greater the efficiency.
BTU
EER =
(2)
TUcooling output
Whelectricy input
Nationally, high efficiency air conditioners have EER values in the range of 16 to 23 [9]. For the
purposes of this study an EER of 20 was chosen as it is near the top in performance within the
high efficiency range. As in the selection of the natural gas furnace efficiency, it is a value that is
realistically to be found in a high efficiency home.
The type of air conditioning system most frequently found in homes is vaporcompression air conditioning (Fig. 1). Vapor compression air conditioning works by circulating
a refrigerant through a closed cycle consisting of a compressor, condenser, throttle, and
evaporator. This cycle allows for the transport of energy from the indoors into the outdoors to
achieve a cooling effect.
W
Compressor
Vapor
,
por
Evaporal o
Condenser
Qcondenser
Qenvironment
Expansion
Liquid + apor
Valve
Uq id
boundary of house
Figure 1. Vapor-Compression Air Conditioning Cycle
4. Ground Source Heat Pump Model
A ground source heat pump (GSHP) is a device that makes use of the earth's relatively
constant ground temperature at some depth in order to heat or cool an enclosed indoor area.
GSHP utilize the same cycle as conventional air conditioners: the vapor-compression
8
refrigeration cycle.
Because GSHP are used to both heat and cool buildings, the cycle is
outfitted so that the direction of heat flow can be reversed depending upon whether there is a
demand for heating or cooling.
The GSHP selected for use in this study is from the Envision model line from the
manufacturer WaterFurnace,which is a large player in the GSHP market. The Envision model
line was chosen as it represents the highest efficiency models that WaterFurnacemanufactures.
The model selected for study was NS048-ECM. This model has mid-ranged air flow capacity
(1500 cubic feet per minute) and represents a high-efficiency model due the use of an electrically
commutated motor which is designed to operate at high efficiencies for all desired speeds.
There are a variety of implementations for GSHP. The most widely applicable is the
ground loop configuration. The ground loop configuration consists of a series of tubes that lie
five to ten feet below ground. Unlike some other configurations, the ground loop consists of a
closed cycle and does not exchange anything with the ground but energy and entropy.
GSHP are characterized by two operating efficiencies, one for heating (COP) and one for
cooling (EER). The COP is defined as the ratio of the heat out to the work in, and in this case
the BTU output to the Watts input.
COP
COP=
BTUheat
-output
k Whelectricity _input
(3)
The EER is the ratio of the BTU of output cooling to the input in kilowatt-hours of electricity,
just as in the case of the conventional air conditioner (see eqn. 2).
In order to determine the most accurate operating conditions for each geographic location
of interest, the COP and EER of the GSHP were related to the average annual ground
temperature. National weather data taken from the U.S. Department of Energy's website [10]
was used as it featured the monthly average 2 meter ground temperatures for a given city. These
monthly averages were averaged to determine an average annual ground temperature.
The 2
meter depth was appropriate as it represents a typical depth of installed tubing in ground loop
GSHP.
In order to relate ground temperature to the COP and EER, the product specification data
was used to create a relationship between the temperature and efficiency.
The product
specification data was taken directly from the specification catalog of the product [11]. The data
is formatted in a table relating the COP/EER to the entering water temperature. Entering water
temperature is defined as the temperature of the water (the system working fluid) as it comes out
of the ground prior to its entering the vapor-compression cycle. Typically GSHP systems are
designed so that the difference between the ground temperature and the entering water
temperature is no more than 8K. In this study, the assumption was made that for the winter
months, the entering water temperature is 5 oF cooler than the ground temperature, and during
the summer months it is 5 oF warmer than the ground temperature.
The product specification data tabulates the entering water temperature in increments of
10 OF. In order to interpolate the values between these ten degree increments, the entering water
temperature was plotted against the corresponding COP and EER values in two separate graphs.
For the plot of the entering water temperature versus COP, the trendline function in Excel was
used to make a power function fit of the data points.
Likewise, for the entering water
temperature versus EER graph, a third degree polynomial function fit was used. The precision of
the trendline functions was determined by eye. For each graph, multiple trendlines of differing
function types were tested to see which best fit the plotted data. These two relationships are
shown in figures 2 and 3 below.
COP vs. Ground Temperature
04218
4218
y = 0.8291x
5
4
©
2
3-
1
00
10
20
30
40
50
60
70
80
90
Ground Temperature (F)
Figure 2. GSHP COP relation to ground temperature
100
EER vs. Ground Temperature
35
30
25
20
y = 3E-05 - 0.0O
15
+ 0.1131x + 29.968
10
5
0
10
20
30
40
50
I
I
I
I
0
60
70
80
90
Ground Temperature (oF)
Figure 3. GSHP EER relation to ground temperature
With the ability to interpolate between the ten degree increments, for any given average
annual ground temperature a specific COP and EER can be defined. Since the COP and EER
describe the overall operating performance: the energy output and energy input, these two values
can be directly used to determine the carbon produced through the use of GSHP.
5. Micro-CHP Model
Micro-Combined Heat and Power (Micro-CHP) is a space heating technology that
simultaneously produces heating and electricity in residential homes. The type of micro-CHP
selected for analysis in this study uses internal combustion engine technology to produce heat
and power. The company ECR Internationalmarkets this product under the name freewatt [12].
Freewatt operates by exclusively using natural gas to run an internal combustion engine
operating on a 4-stroke Otto cycle. This, in turn, drives an electrical generator.
The heat of
combustion that is not transferred into work is captured and through means of a heat exchanger,
is circulated throughout the ductwork of the home. Due to the sizing of the Micro-CHP system,
the heat generated from the internal combustion engine may not always be enough to meet the
heat demand of the home. Therefore, the power generation system is paired with a high
efficiency natural gas fired furnace. This auxiliary furnace operates only when the heat from the
power generation unit does not meet the total demand.
Because of freewatt's two-stage operation (power generation plus auxiliary heating
furnace), the determination of the precise operating characteristics is based upon multiple
variables such as seasonal variation in heat demand, home size and heating intensity required.
Since the goal of this report is to characterize each the heat demand of each city by its number of
heating degree days, a model was needed to relate the operating characteristics of the freewatt
system to the value of heating degree days for a given location. A model which related these
two quantities was provided to me by the manufacturer offreewatt. This model is based upon the
operating characteristics of a variety of actual system installations.
Based on the data from
actual installations, the model determines how much heat is derived from the power generation
module and the auxiliary furnace. This then allows for an accurate prediction of this breakdown
for the weather data of any city.
The model was used to extract operating data for 26 cities. The values derived from the
model were heating degree days, electricity produced by the power generation module and the
total annual gas consumption of the system (power generation plus auxiliary furnace). Two
graphs were constructed from this data. Since the relationship between heating degree days and
operating characteristics was desired, heating degree days was plotted against the electricity
production as well as the annual gas consumption. Linear trendlines were created on both of
these plots so that general relationships could be extracted from the data (Figures 4 & 5).
Heating Degree Days vs. MCHP Electricity Production
9000
=
y 0.8082x
8000
7000
6000
a
4000
S2000
1000
0
0
2000
4000
6000
8000
10000
12000
Heating Degree Days
Figure 4. Relation of Heating Degree Days with MCHP Electricity Production
Heating Degree Days vs. MCHP Annual Gas Consumption
200
=
y 0.0175x
180
160
o
140
120
100
S
.
80
60
20
0
0
2000
4000
6000
8000
10000
12000
Heating Degree Days
Figure 5. Relation of Heating Degree Days with MCHP Annual Gas Consumption
With the creation of these relationships, the amount of fuel consumed and electricity produced
can be calculated for any location, as heating degree days are tabulated by city. The values of
fuel and electricity consumption allow for the determination of the carbon production associated
with the use of Micro-CHP.
Unlike GSHP, Micro-CHP technology only provides for heating, rather than for both
heating and cooling. Therefore, a different system needs to be used to meet the cooling demands.
In this study a high efficiency vapor-compression air conditioner with an EER of 20 was used.
This is the same system that was used in the conventional system home model.
6. House Model
A single-family detached home was used as a model structure in this analysis. There are
72.1 million homes in this class representing the majority, or 65%, of the housing units in the
United States [13]. The average home is 2,349 square feet in size and was built around 1970
[14]. This average home size and age were used in the making of this model.
In order to characterize the heating demand properly, a heating intensity required for this
type of home structure was determined. For homes built around the year 1970, the design
characteristic for this model, a heating intensity of 5.6 BTU/HDD*sq-ft is required [15], where
HDD represents annual heating degree days and sq-ft is the total heated square feet. Heating
degree days are a way to define the demand of heat. The amount of heating degrees in a single
day is determined by the difference between the standard reference value of 65 0F and the average
daily temperature. For the number of annual heating degree days, the heating degrees of all days
are summed.
The cooling intensity was determined in a slightly different way.
The only cooling
intensity discovered in literature was expressed in the units of kWh/CDD*sq-ft [16]. To convert
this quantity from an electrical intensity to a thermal intensity, with units of BTU/CDD*sq-ft, an
assumption needed to be made concerning the performance of the average installed air
conditioner found in a home in the United States. This is because the value of the cooling
intensity in the literature was indeed based upon the average implementation. Based on reports
from the Energy Information Administration, it was assumed that the average installed air
conditioner operates with an EER of 10. A lower EER was used here compared to the one
defined for the vapor-compression air conditioner (20 EER) that was used in the various models.
This is because the model is supposed to represent a high-efficiency home, whereas the given
data here required the use of an EER representative of the average installed system. Using this
information, the thermal cooling intensity was found to be 7.8 BTU/CDD*sq-ft. This cooling
intensity is higher than the heating intensity likely due to the negative effects that sun radiation
has on the cooling process within the home.
Similar to heating degree days, cooling degree days are a way to characterize a home's
cooling demand. Cooling degree days use a reference temperature of 65 0F and are defined as the
difference between 65°F and the average daily temperature.
Since electricity consumption from appliances and lights and such contribute to a home's
energy profile, and subsequently its carbon profile, this electricity usage must be taken into
account. The average annual electric demand in residential homes to operate all devices (except
electric heaters and cooling equipment) in the United States was 7989 kWh for 2001 [17], the
most recent year for which data was available. This number was taken as the assumed electrical
load for all uses, except heating and cooling. In order to accurately reflect the national variations
in electricity usage, the electricity used for cooling is added onto the base consumption for each
location.
7. Carbon Comparison Calculations
7.1 Carbon Produced by Home with Conventional Heating & Cooling System
In order to determine the amount of carbon produced by operating the previously defined
conventional heating system, the annual heating load must be calculated. This is determined
using the assumed heating intensity (5.6 BTU/HDD*sq-ft) the house size (2,349 sq-ft) and the
number of heating degree days. Annual heating loads ranged from about 20 million BTU in the
warmer climates, to 100 million BTUs in the colder climates.
Once the heating load was
determined, the annual gas consumption was calculated. This study assumes a conventional
natural gas warm-air furnace to operate at an efficiency of 95%. To determine the annual gas
consumption, the annual heating load was divided by the 95% operating efficiency.
Since
117.08 lbs of CO 2 are produced for every million BTU of natural gas burned, the amount of
carbon produced annually by the conventional heating system was calculated by multiplying this
conversion factor by the annual gas consumption in millions of BTU. The pounds of CO 2
produced annually ranged from about 2,000 lbs to 10,000 lbs for the different geographical
locations.
Likewise, for the conventional cooling system, the annual cooling demand was
determined by using the assumed cooling intensity (7.7 BTU/CDD*sq-ft), the home size (2,349
sq-ft) and the annual number of cooling degree days.
Using the defined EER of 20, the
electricity consumed by the conventional cooling system was calculated by dividing the cooling
demand by the EER. The CO 2 produced from operating the cooling system is directly dependent
on the power plants from which the power is sourced. Therefore, to determine the amount of
CO 2 produced, the annual electricity consumed by the cooling system is multiplied by an
assumed carbon output emission rate for a particular location. The amount of CO 2 produced
from annual domestic cooling ranged from as low as about 100 lbs per year to as high as about
6000 lbs per year, depending on the location and carbon emission characteristic of the local grid
supplied electricity.
The CO 2 produced for the general appliance electric consumption was calculated in
exactly the same way as the CO 2 produced as a result of electricity use of the cooling system.
Therefore, for the assumed annual amount of electricity consumed (7989 kWh), the amount of
CO 2 produced ranged from 7,000 to 16,000 lbs.
To determine the annual carbon footprint of a home with a conventional heating and
cooling system, the CO 2 produced by the heating and cooling system and the annual general
appliance electric consumption were summed. These values ranged from about 10,000 lbs to
30,000 lbs.
7.2 Carbon Produced by GSHP Home
As discussed previously in the explanation of the GSHP model, the heating COP and
cooling EER of the GSHP in each location were determined based on a relationship formed with
the average annual ground temperature. To determine the annual electricity required for the
GSHP in heating mode, the annual heat demand was divided by the heating COP. The
calculation of the annual heat demand remains the same as for the conventional heating system,
as described above, as it is dependent on only the weather and house model which remain the
same throughout the investigation of all of the technologies. To find the amount of CO 2 produced
by GSHP in heating mode, the electricity consumed is converted to lbs of CO 2 via the grid
supplied electric power carbon emission output rate as described earlier.
The calculation of the CO 2 produced by the GSHP in cooling mode is nearly identical to
that of the heating mode. To determine the annual electricity consumption for cooling, the annual
cooling demand was divided by the EER. This annual electricity demand was then converted in
pounds of CO 2 via the emission output rate for each city.
The CO 2 produced from the operation of the GSHP in heating and cooling modes was
added to the CO 2 produced by the general electric appliance consumption to determine the
annual carbon footprint. The calculation for the CO 2 from the general appliance electric
consumption remains unchanged from the analysis of the conventional system. The total annual
carbon footprints ranged from under 10,000 lbs of CO 2 to over 30,000 lbs of CO 2 for the model
home with a ground source heat pump used for heating and cooling.
7.3 Carbon Produced by Micro-CHP Home
Based upon the results of the model constructed for the micro-CHP system, the annual
electricity production and natural gas consumption for each location were determined. Using the
conversion factor of 117.08 lbs of CO 2 per 1 million BTU natural gas, the amount of CO 2
produced by operating the micro-CHP system was calculated.
Since this study pairs the micro-CHP system with a conventional air conditioning system,
the carbon produced by the operation of the air conditioning is calculated exactly the same way
as described earlier in the section on the conventional energy systems.
The micro-CHP produces a substantial amount of useful electricity, ranging from 1000
kWh to 6000 kWh annually, this must be taken to account when considering the amount of
electricity required from the grid.
In order to account for this, the amount of electricity
generated by the Micro-CHP was subtracted from the pre-determined general appliance annual
demand. The CO 2 associated with this net electric intake is calculated by multiplying it by an
appropriate CO 2 output emission rate for grid supplied electricity.
7.4 Electric Grid Carbon Characteristic:Impact on Analysis
As the discussion above regarding the calculation of the total carbon emissions profile for
the three technology alternatives (conventional, GSHP, micro-CHP) indicates, the results of their
comparative performance depends on the assumed carbon characteristic of the grid electricity.
In performing these analyses, it became clear that this specific value assumed for this carbon
characteristic would significantly influence the comparative performance of these technology
alternatives with regard to their impact on carbon emissions. Simply stated, a low assumed grid
electricity carbon characteristic favors the use of a ground source heat pump as a carbon
reduction strategy, while assumption of relatively high carbon production characteristics of the
grid favors the micro-CHP alternative, as it displaces (rather than increases) carbon intensive
electric power production. The net carbon production characteristic of micro-CHP system
generate electricity itself is low, even though it operates on natural gas fossil fuel. This is
because its efficiency in use of natural gas is effectively 90%, as it produces electric power on
top of the already in-place consumption of gas for heating.
Compared to the determination of the heating and cooling loads and the power
consumption of these demands, which is rather straightforward, the basis for making a
reasonable assessment of the grid carbon characteristic is not clear and appears to be a debatable
subject.
Does one assume that all electric conservation (or use) technologies add to the
incremental reduction (or use) of fossil fuels where all low carbon producing power stations will
always be used as a priority?
Or does one assume that the average is just that, the average, and
nothing more can be reasonably assumed?
To address this issue, two different assumptions of grid electric carbon profiles have been
assumed for the displaced electricity generated by micro-CHP and the increased electricity used
by GSHP. These are
1) Local Grid average provided by Environmental Protection Agency
2) Local Grid Fossil Characteristic as provided by The Emissions & Generation
Resource Integrated Database
The different specific values for the different geographical areas are provided in Appendix B.
The local grid average electricity emission profile takes into account all types of electric
production: coal, gas, oil, nuclear, renewables etc., as present in the local area. The average is
computed from the total generation contributed by each type of plant. An alternative method of
assessing the impact of power conservation measures on carbon emissions from grid electricity
production is to assume that all conservation (or increased usage) results in the offset (or
increase) of the use of fossil fuel generation. The rationale for this is that if carbon reduction is
a primary driver for conservation, then it is the reduction of the fossil fuel use that will be
achieved.
Other types of low carbon generation would continue, such as hydroelectric, nuclear
and renewables. Personal correspondence with one energy analyst, Bruce Hedman, active on the
national level with regard to combined heat and power has suggested that this alternative method
is the most rational basis for assessing impacts involving use of combined heat and power on
total carbon emissions [18]. Applying the above rationale to GSHP would imply that the
additional electric demand generated from the use of GSHP would be met by increasing the use
of fossil fuel plants. This is largely due to the relative ease at which the output of fossil fuel
plants can be scaled. At this current point in time it may be reasonable to assume that any
increased grid electric demand from the increased use of GSHP would be met by electricity
produced by fossil fuel plants.
The method used to determine the annual CO 2 generation for homes with micro-CHP
using the fossil fuel emission rate for the local grid electricity only slightly differs from the
method used to determine the same output using grid average data. The method differs in the
way the annual CO 2 production associated with electric generation is calculated.
First the
average annual appliance electric consumption, 7989 kWh, is multiplied by the local grid
average CO 2 emission rate for the specific geographical region. This assumes the electricity
taken from the grid for appliance use resembles the local grid average emission profile. Second,
the electricity produced by the micro-CHP (or the displaced electricity) is multiplied by the local
fossil fuel CO 2 emission rate [19]. Finally, these CO 2 emissions savings associated with the
displaced electricity is subtracted from the CO 2 associated with the annual average electric
consumption. The result is the net CO 2 generation associated with the model home's annual
appliance electric consumption. To determine the total annual CO 2 produced by homes with
micro-CHP, the CO 2 production associated with the use of natural gas in the micro-CHP system
and the electricity use associated with appliance use and cooling are summed.
The method used to determine the annual CO 2 generation for homes with GSHP uses the
local grid fossil fuel emission rate to calculate the CO 2 generated as a result of the GSHPs use of
electricity to meet the heating and cooling requirements. To calculate the GSHPs annual CO 2
generation, the annual electricity required for running the GSHP in heating and cooling mode is
multiplied by the local fossil fuel CO 2 emission rate to determine the CO 2 associated with heating
The CO 2 emissions associated with the electricity used for appliances are
and cooling.
determined by multiplying the annual appliance electric use by the local grid average CO 2
emission rate.
The local grid average emission rate is used in this case because the annual
appliance electric use does not represent part of the increased demand of electricity due to the
use of GSHP. To determine the annual CO 2 generated for the model home with GSHP, the CO 2
generation associated with heating and cooling is added to the CO 2 generation associated from
appliance electric use.
8. Results and Conclusions
In this study an attempt has been made to resolve the actual relative merits of GSHP and
micro-CHP systems in lowering the carbon foot print of the typical America home. If one
assumes electricity is available from carbon-free sources such as nuclear power, wind, hydro
power, or the sun, then the answer is obvious. GSHP can have near zero net carbon
emissions.
In contrast, micro-CHP systems run on natural gas and thus inevitably produce
some level of carbon emission as this carbon based fuel is burned.
Thus, with zero carbon
electricity available, the clear advantage goes to the ground source heat pump.
The reality, however, is not that simple. The great majority of electricity in the United
States is generated using fossil fuels. Indeed, about half is generated using coal, which is the
carbon emissions intensive source of electric energy. Thus, sorting out the comparison of the
"real" relative merits of GSHP and micro-CHP sources is ultimately based on the assumption of
how electricity is produced by the utility grid.
GSHP substantially increase electricity use from
the grid while micro-CHP systems substantially reduce it. Relative merits depend on assessing
the carbon emission characteristics of locally obtained electricity.
In this study it has been possible to characterize well the thermal and energy performance
of a model home in different locations in the United States with conventional, GSHP, and microCHP energy systems.
What has been more difficult is to characterize the carbon characteristic
of the locally supplied electricity from the grid that is part of net carbon emission
calculation. The grid electricity carbon characteristic is critical to the results of the comparison
of these home energy systems. Determining exactly how much carbon emissions is saved for
each kilowatt-hour reduction in electric use was found to be an open and debatable question in
the field of energy and environmental analysis. So what has been done here has been to look at
several different reasonable assumptions regarding the relationship between grid electric power
production and carbon emissions.
The particular cases of interest are 1) the local average
carbon emissions for electric power from the grid and 2) the local average of fossil fuel electric
generation. Both of these characterizations have been reported by government agencies for use
in assessing electric power and carbon emissions issues.
The first assumption is the most simple. It is the simple average of all power
generation.
The second is applied as it is more relevant to the idea that a national carbon
reduction strategy may be based on reducing fossil-carbon-based electric generation, not electric
generation itself. Thus, both assumptions have merit. It depends on the perspective.
8.1 Results Using Average C0
2
Emissions Rate for Local Grid Electricity
The results for the assumption of local grid average carbon emissions for all electric
savings (and increases) are depicted in graphical forms in a series of maps. The first (Fig. 6)
shows the state averages of the relative magnitudes of the annual CO 2 generated for the
conventional, GSHP and micro-CHP energy systems as installed in the model home.
Conventional
Figure 6. Comparative energy-related CO 2 emissions for model home for GSHP,
micro-CHP and conventional systems by state using local grid average CO 2
emission rates
Figure 6 is useful in determining the relative impact of each technology as implemented in a
particular state. In nearly all cases it is evident that GSHP and micro-CHP produce less CO 2 than
the conventional system; however there are some exceptions. In the north Midwest, the CO 2
produced by GSHP exceeds that produced by the conventional system, highlighting the dramatic
impact carbon intensive fossil fuel based electric generation has on the merits of GSHP.
In order to visualize the trends of CO 2 intensity among each technology, two graphics
instituting color trends were created as Figures 7 and 8.
5,000 lbs
yi
30,000Olbsyr
Figure 7. Total annual energy-related CO 2 for Model homes with GSHP using
local grid average CO 2 emission rates
10,000
Ibs i
20.000lbsyr
Figure 8. Total annual energy-related CO 2 for Model homes with micro-CHP
using local grid average CO 2 emission rates
The darker areas depict more CO 2 intensive areas, while the lighter areas depict less CO 2
intensive areas. The geographical color trends for both technologies tend to follow the same
pattern. This is largely due to the inherent carbon characteristics of the local electric grid. The
Midwest, with its strong reliance on fossil fuel based electric generation, shows a more CO 2
intensive profile.
However useful the trends in CO 2 generation for both technologies are, the more
interesting result comes from the direct comparison of the technology on a state by state basis.
This approach answers the question of which technology is better implemented in each state
based upon its CO 2 generation profile. In order to depict this graphically, GSHP and micro-CHP
were directly compared to the carbon profile of the conventional system. This was done in each
state by taking the CO 2 generated by the conventional system and subtracting the CO 2 generated
by the GSHP in one case and subtracting the CO 2 generated by the micro-CHP in the other case.
The resulting values represent the differences in CO 2 generation for each technology as
compared to the conventional system in a particular state. In order to determine which
technology is better suited for a given state, a ratio of the GSHP difference to the micro-CHP
difference was made. A ratio of 1:1 indicates indifference in technology preference. In this case
a ratio greater than one indicates a preference to GSHP while a ratio less than one indicate
preference to micro-CHP. A graphic depicting the resulting trends in ratios is shown in Fig. 9.
-
McHP
Indifferent GSrp
Figure 9. Best technology choice by state based upon annual CO 2 emissions
using grid average emissions analysis for Micro-CHP
Figure 9 indicates a preference to micro-CHP in the middle of the country, a preference to GSHP
on the coast, and some indifference in the south. The high concentration of fossil fuel power
generation in the Midwest favors the implementation of MCHP while the lower carbon intensive
coastal regions favor GSHP. As an aside, the portrayal of micro-CHP better suited for Hawaii is
somewhat incorrect. Hawaii has an annual heating demand of 0 BTU. Thus, the annual CO
2
generated by micro-CHP and the conventional energy system are equal since there is no heating.
However, because the CO 2 generated by GSHP in Hawaii was greater than conventional/microCHP it is better suited for the micro-CHP option for the purposes of figure 9. In reality, a microCHP system would never be utilized as there is zero demand for heat.
8.2 Results Using Fossil Fuel Generation CO 2 Emissions Rate of Local Grid
Electricity
The results for analysis using the fossil fuel plant CO 2 emission approach are shown
graphically in the same series of maps as used above. Figure 10 shows the relative CO
2
generation of GSHP, micro-CHP and the conventional system implemented in the model home.
( olventi onlI
Axe
MICHP
GSHP
Figure 10. Comparative energy-related CO2 emissions for model home for
GSHP, micro-CHP and conventional systems by state using local fossil fuel plant
CO 2 emission rates
The most noticeable difference between fig. 10 and fig 6. is that the CO 2 generated by GSHP
implementation exceeds that of the conventional system in many instances, while the CO 2
system. The
generated by micro-CHP implementation is typically far less than the conventional
trends in GSHP and micro-CHP are portrayed in figures 11 and 12.
S10,000
l
br
20,000 Ibs'yr
y
Figure 11. Total annual energy-related CO 2 for model homes with micro-CHP
using local fossil fuel plant CO2 emission rates
5.000 lbs yr
3
-i0
0lbs
r
Figure 12. Total annual energy-related CO2 for model homes with GSHP using
local fossil fuel plant CO2 emission rates
Compared to the CO 2 generation trend of micro-CHP utilizing local electric grid average
CO 2
emission data, fig. 11 shows micro-CHP in a much more favorable light, displaying much more
pink, indicating lesser magnitudes of CO 2 emissions. On the other hand, fig. 12 shows much
darker areas over most of the country, indicating that this fossil fuel CO 2 emission based form of
analysis is not favorable to GSHP.
To further emphasize the favorable light that is cast on micro-CHP using this form of
analysis, figure 13 depicts micro-CHP as the best-choice technology for every state.
MCHP bidiffercnt ;SBIf
Figure 13. Best technology choice by state based upon annual CO 2 emissions
using grid average emissions analysis for Micro-CHP
References
[1] Lund, J., B. Sanner, L. Rybach, R. Curtis, and G. Hellstrom. 2004. "Geothermal (Ground
Source Heat Pumps) A World Overview." GHC Bulletin. pp. 1-10.
[2] Hanova, J., and H. Dowlatabadi. 2007. "Strategic GHG reduction through the use of ground
source heat pump technology." Environmental Research Letters. pp. 1-8.
[3] Energy Center of Wisconsin. 2000. "Emissions and Economic Analysis of Ground Source
Heat Pumps in Wisconsin." pp. 1-68.
[4] Onovwiona, H. I., and V. I. Ugursal. 2004. "Residential cogeneration systems: review of the
current technology." Renewable and Sustainable Energy Reviews. 10 pp. 389-431.
[5] Pehnt, Martin. 2008. "Environmental impacts of distributed energy systems - the case for
micro-CHP." Environmental Science and Policy. 11 pp. 25-37.
[6] Peacock, A. D., and M. Newborough. 2005. "Impact of micro-CHP systems on domestic
sector CO 2 emissions." Applied Thermal Engineering 25 pp. 2653-2676.
[7] "How clean is the electricity I use?" U.S. Environmental Protection Agency.
<http://www.epa.gov/cleanenergy/energy-and-you/how-clean.html>.
Information
[8] "2005 Residential Energy Consumption Survey."Apr. 2008. Energy
0 5/hc 2 0 0O55-tables/hc4spacehea
Administration.<http://www.eia.doe.gov/emeu/recs/recs20
ting/pdf/tablehc2.4.pdf>.
[9] "High-efficiency 16 to 23 SEER Central Air Conditioner Review." Product Reviews and
Reports - ConsumerSearch.com. <http://www.consumersearch.com/central-airconditioners/high-efficiency- 16-23-seer-central-air-conditioner>.
[10] "EnergyPlus: Weather Data." U.S. DOE Energy Efficiency and Renewable Energy (EERE).
<http://apps 1.eere.energy.gov/buildings/energyplus/cfm/weather data3.cfm/region=4no
rthandcentral america wmo region_4/country=1 usa/cname=USA>.
[11] WaterFurnace. Envision Residential Specification Catalog.
<http://secure.waterfumrnace.com/docs/FB507406666/manuals/envision/SP 1585.pdf>.
[12] Freewatt Eco-Friendly Heating & Power Systems. 20 Jan. 2009 <http://freewatt.com>.
[131 "Housing Unit Characteristics by Type of Housing Unit." Energy Information Agency.
<http://www.eia.doe.gov/emeu/recs/recs2005/hc2005 tables/hc housingunit/pdf/tablehc
2.1.pdf>.
[14] Adler, Margot. "Behind the Ever-Expanding American Dream House :NPR." NPR.
<http://www.npr.org/templates/story/story.php?storyld=5525283>.
[15] Comprehensive Energy Use Database.
<http://oee.nrcan.gc.ca/corporate/statistics/neud/dpa/trendsres_on.cfm>.
[16] "Electric Air-Conditioning Energy Consumption in U.S. Households by Type of Housing
Unit." 2001. Energy Information Agency.
<http://www.eia.doe.gov/emeu/recs/recs2001/ce df/aircondition/ce34c_housingunits2001 .pdf>.
[17] "U.S. Household Electricity Data: A/C, Heating, Appliances 2001." Official Energy
Statistics from the U.S. Government. Energy Information Agency.
<http://www.eia.doe.gov/emeu/reps/enduse/er01 us tab .html>.
[18] "Discussion of Fossil Fuel Replacement Approach to Carbon Emissions Reductions."
E-mail interview. 3 Apr. 2009.
[19] EGRID2006 Version 2.1. 2007.
Appendices
Appendix A: Micro-CHP and GSHP Annual CO 2 Emission Comparison by State
Note: Magnitudes of emissions may not be compared between figures, only within the figure itself
RED: Annual micro-CHP CO 2 emissions
Annual GSHP CO 2 emissions
Appendix A.1: Relative magnitudes of GSHP and micro-CHP CO 2 emissions
in cities in Arizona and New Mexico
Appendix A.2: Relative magnitudes of GSHP and micro-CHP CO 2 emissions
in cities in California and Nevada and Utah
Grand Rapids, MI
Madison, WI
IN
Columbus,
Springfield,
IL
Appendix A.3: Relative magnitudes of GSHP and micro-CHP CO 2 emissions
in cities in Wisconsin, Michigan, Illinois, Indiana, Ohio, Kentucky and West
Virginia
Appendix A.4: Relative magnitudes of GSHP and micro-CHP CO 2 emissions
in cities in Wyoming and Colorado
32
Charleston, SC
Jackson, MS
Gulfport, MS
Mia i, FL
Appendix A.5: Relative magnitudes of GSHP and micro-CHP CO 2 emissions
in cities in Mississippi, Alabama, Georgia, South Carolina and Florida
Appendix A.6: Relative magnitudes of GSHP and micro-CHP CO 2 emissions
in cities in Nebraska, Iowa, Kansas and Missouri
Appendix A.7: Relative magnitudes of GSHP and micro-CHP CO 2 emissions
in cities in North Dakota, South Dakota and Minnesota
Appendix A.8: Relative magnitudes of GSHP and micro-CHP CO 2 emissions
in cities in Maine, New Hampshire, Vermont, Massachusetts, Rhode Island,
Connecticut, New York, New Jersey and Pennsylvania
36
Appendix A.9: Relative magnitudes of GSHP and micro-CHP CO 2 emissions
in cities in Washington, Oregon, Idaho and Montana
Smith,
j
le Rock,
New
Appendix A.10: Relative magnitudes of GSHP and micro-CHP CO
2
emissions in cities in Oklahoma, Arkansas and Louisiana
Appendix A.11: Relative magnitudes of GSHP and micro-CHP CO
2
emissions in cities in Texas
ginia Beach, VA
Nashville, TN
Raleigh, NC
Appendix A.12: Relative magnitudes of GSHP and micro-CHP CO 2
emissions in cities in Virginia, Tennessee and North Carolina
Appendix B: CO 2 emissions by city for grid average and fossil fuel plant emission rates
City
Birmingham, AL
Montgomery, AL
Anchorage, AK
Flagstaff, AZ
Phoenix, AZ
Tucson. AZ
Fort Smith, AR
Little Rock, AR
Fresno, CA
Long Beach, CA
Los Angeles, CA
Sacremento. CA
San Diego, CA
San Franciso. CA
San Jose, CA
Colorado Springs, C(
Denver, CO
Bridgeport, CT
Washington DC
Wilmington, DE
Jacksonville, FL
Miami, FL
Atlanta, GA
Augusta, GA
Honolulu, HI
Boise, ID
Idaho Falls, ID
Chicago, IL
Springfield, IL
Fort Wayne, IN
Indiannapolis, IN
Waterloo, IA
Des Moines. IA
Topeka, KS
Witchita, KS
Lexington, KY
Louisville, KY
New Orleans, LA
Shreveport, LA
Portland, ME
Baltimore, MD
Boston, MA
Worcester, MA
Detroit, MI
Grand Rapids. MI
Minneapolis, MN
Rochester, MN
Gulfport, MS
Jackson, MS
Kansas City, MO
St. Louis, MO
Billings, MT
Missoula, MT
Lincoln, NE
Omaha, NE
Las Vegas, NV
Reno, NV
Manchester. NH
Newark, NJ
Albuquerque. NM
Albany, NY
Buffalo, NY
New York, NY
Charlotte, NC
Raleigh, NC
Bismarck, ND
Fargo, ND
Cleveland, OH
Columbus, OH
Oklahoma City, OK
Tulsa, OK
Portland, OR
Salem, OR
Philadelphia, PA
Pittsburgh, PA
Providence, RI
Charleston, SC
Columbia, SC
Rapid City, SD
Sioux Falls, SD
Memphis, TN
Nashville, TN
Austin, TX
Dallas, TX
El Paso, TX
Fort Worth, TX
Houston, TX
San Antonio, TX
Provo, UT
Salt Lake City, UT
Burlington, VT
Richmond, VA
Virginia Beach. VA
Seattle, WA
Spokane, WA
Charleston, WV
Parkersburg, WV
Madison, WI
Milwaukee, WI
Casper, WY
Cheyenne, WY
Heating
65F
2844
2269
10911
7322
1552
1752
3336
3354
2650
1606
1245
2843
1507
3042
2303
6473
5505
5461
5005
4940
1327
206
3095
2547
0
5833
7967
6127
5558
6209
5577
7415
6710
5243
4791
4783
4514
1465
2167
7498
4729
5621
6848
6419
6801
8159
8227
1551
2300
5161
4750
7265
7931
6012
6601
2601
6022
7554
5034
4292
6888
6927
4848
3218
3514
8968
9254
6154
5702
3695
3680
4792
4852
4865
5278
5972
1904
2598
7324
7838
3227
3696
1737
2290
2678
2382
1434
1570
5907
5983
7876
3939
3495
4727
6835
4590
4817
7730
7444
7555
7255
Cooling
Base Temp
1928
2238
0
140
3508
2314
2022
1925
1671
985
1185
1159
722
108
587
461
742
735
2898
992
2596
4038
1589
1995
4221
714
269
925
1116
748
974
675
928
1361
1628
1140
1288
2706
2538
252
1108
661
387
654
575
585
474
2645
2316
1421
1475
498
188
1187
949
2946
329
328
1024
1316
574
437
1068
1596
1394
488
537
613
809
1876
1949
300
232
1104
948
532
2354
2087
661
719
2029
1694
2903
2755
2098
2587
2889
2994
745
927
396
1353
1422
183
388
1055
1045
460
450
458
327
Zip Code
36110
35214
99501
86004
85020
85714
72904
72210
93705
90805
90025
95823
92118
94115
95120
80917
80206
06608
20018
19810
32222
33137
30315
30909
96817
83713
83404
60617
62712
46808
46220
50703
50310
66618
67211
40502
40220
70126
71103
04107
21210
02115
01602
48205
49505
55420
55904
39503
39202
64111
63112
59102
59803
58520
68106
89110
89511
03103
07107
87112
12208
14210
10010
28215
27613
58501
58102
44116
43213
73110
74126
97214
97301
19102
15210
02906
29407
29209
57702
57106
38115
37211
78704
75218
79911
76118
77004
78224
84604
84101
05401
23228
23459
98119
99203
25311
26101
53717
53205
82630
82001
Local Grid Average
CO 2 Output
Emission Rate
(Ibs/MWh)
1490
1490
1257
1254
1254
1254
1761
1135
879
879
879
879
879
879
879
2036
2036
909
1096
1096
1328
1328
1490
1490
1728
921
921
1556
1844
1556
1556
1814
1814
1971
1971
1495
1495
1135
1761
909
1096
909
909
1641
1641
1814
1814
1490
1135
1971
1844
921
921
1814
1814
1254
921
909
1096
1254
820
820
922
1146
1146
1814
1814
1556
1556
1761
1761
921
921
1096
1556
909
1146
1146
2036
1814
1495
1495
1421
1421
1254
1421
1421
1421
921
921
909
1146
1146
921
921
1556
1556
1859
1556
2036
921
Local Grid Fossil
Fuel CO 2 Output
Emission Rate
(Ibs/MWh)
1949
1949
1435
1743
1743
1743
1863
1642
1437
1437
1437
1437
1437
1437
1437
2162
2162
1431
1687
1687
1447
1447
1949
1949
1775
2032
2032
2030
2117
2030
2030
2350
2350
2344
2344
2126
2126
1642
1863
1431
1687
1431
1431
1765
1765
2350
2350
1949
1642
2344
2117
2032
2032
2350
2350
1743
2032
1431
1819
1743
1794
1794
1819
1913
1913
2350
2350
2030
2030
1863
1863
2032
2032
1687
2030
1431
1913
1913
2162
2350
2126
2126
1673
1673
1743
1673
1673
1673
2032
2032
1431
1913
1913
2032
2032
2030
2030
2249
2030
2032
2162
Appendix C: Micro-CHP Total Carbon Profile Data
Ciies
Birmingham,
AL
AL
Montgomery,
Anchorage,
AK
FlagstaffAZ
Phoenix,AZ
Tucson,AZ
FortSmithAR
Littl Rock,AR
Fresno,CA
LongBea..h,CA
LosAngeles,CA
scrmento. CA
SanDiego, CA
SanFranciso,CA
SanJose, CA
ColoradoSpring.,CO
Denver,CO
Bridgeport,
CT
Washington
DC
Wilrington,DE
Jacksonvile,FL
Miami,
FL
AtlantaGA
Augusta,
GA
Honolulu,
HI
Bos, ID
IdahoFals. 10
Chicago,IL
Springfield,
IL
FoilWayne,IN
tadiannapolis,
IN
Waterloo,
IA
D1 Moines,
IA
Topeka,KS
Witchita,
KS
Lexington,
KY
Louisille,KY
NewOdans. LA
Shreveport,
LA
Portnd. ME
Batimore,MD
Boston,.MA
Worcester,MA
Detroi, Mi
GrandRapids,MI
Minneapolis,
MN
Rochester,MN
Gullport.
MS
Jakson, MS
KansasCity,MO
St. Louis,
MO
Billing.,MT
Missoula,MT
Lincoln.
NE
Omaha,NE
LasVegas, NV
Reno.NV
Manchester.
NH
NewakJ
Alb.q'eque, NM
Albany,NY
Buffalo.
NY
NewYork,NY
C ro58e,NC
Raleigh,NC
Bismarck,N0
Fargo.ND
Cleveland.,
0
Columbus,
OH
OklahomaCity,OK
Tull, OK
Portland,
OR
Sale', OR
Philadlphia,PA
Pittsburgh,
PA
Providen-e,RI
Charleston,.SC
Columbia,
SC
RapidCity,SO
SiouxFall, SO
Memphis,
TN
Nashvile,TN
Austin,TX
Dallas.TX
El P.11.TX
FortWorth,TX
Houston,TX
SanAnton!, TX
Prow. UT
SaltLake City,UT
Burlington.
VT
Richmond,
VA
Virginia
Beach,VA
Seatae.,WA
Spoke, WA
Charleston,VWV
Parker s burg,WV
Madis,88W,
Milaukee, Wl
Casper,zVz
Cheyenne.WY
Annual Electricty
Annual Gas
Produced byMCHP Consump
by
byon
(kWhr)
MCHP(10-6 TU)
2298.5
18338
8816.3
5917.6
12543
14160
2696.2
2710.7
2141.7
1298.0
1006.2
2297.7
1218.0
24585
1861.3
52315
44491
4413.6
4045.0
3992.5
1072.5
166.5
2501.4
20585
00
4714.2
6438.9
401.8
44920
5018.1
4507.3
598928
54230
42374
3872.1
3865.6
3648.2
11840
17514
60589
3822.0
4542.9
5534.6
51878
54966
6594.1
6649.1
12535
1858.9
4171,1
3839,0
5871.6
64O9.8
4858.9
53349
21021
4867.0
61051
40685
3468.8
55669
5598.4
3918.2
2600.8
28400
72479
74791
4973.7
46084
29863
2974.2
38729
3921.4
3931.9
4265.7
48266
1538.8
20997
59193
63347
2608.1
2987.1
1403.8
1850.8
2164.4
1925.1
1159.0
1268.9
4774.0
4835.5
63694
3153,5
28247
38204
5524.0
3709.6
3893.1
6247.4
60162
61060
5863.5
49.8
397
1909
1281
27,2
30.7
58.4
58.7
46.4
281
21.8
49.8
26.4
53.2
403
1133
98.3
956
87.6
86.5
232
3.6
54.2
44.6
0.0
102.1
139.4
107.2
97.3
1087
97.6
129.8
117.4
91.8
83.8
83.7
790
25.6
37.9
131.2
828
98.4
119.8
112.3
119.0
142.8
144.0
27,1
403
90.3
83.1
1271
138,8
105,2
1155
455
105.4
132.2
881
751
1205
121.2
84.8
56.3
61 5
1569
161.9
107.7
998
64.7
64.4
83 9
84.9
85.1
92.4
104.5
33.3
455
1282
137.2
565
64w7
30.4
401
49
41.7
25.1
275
103.4
104.7
137.8
68.9
61.2
82.7
119.6
80,3
843
1353
130.3
1322
1270
Annual Carbon
Produced by
NaturalGas (Ib.)
Electricity
AnnaulCO2
Annual Cooling Load Requiredfor
Produced from
(10-6 STU)
Cooling (kWhr) Cooling (Ibs)
5827.1
4649.0
22355.5
15002.0
3179.9
3589.7
68351
68720
5429.6
3290.5
2550.9
5825.0
3087.7
6232,8
4718.6
132625
112792
11189.0
10254.7
10121.6
2718.9
422.1
63413
5218.5
0.0
11951.2
163236
12553.6
113878
127216
11426.7
15192.6
137401
10742.4
9816.3
97999
92487
3001.6
4440.0
153627
96892
115169
140309
131519
13934.6
16717.0
16856.3
31778
47125
10574.4
9732.3
1489.3
16249.8
123160
135248
5329.2
12338.
194774
10314.2
87939
14112.8
14192.7
9933,1
65934
71996
18374.5
18960.5
12608.9
11682.8
7570.7
75400
98183
99413
9967.9
10814.1
12236.0
3901.1
5323.0
1506.1
16059.3
6611.8
7572.7
358.59
4692.0
5487.0
48805
2938.1
32168
121029
12258.6
16137,1
8070.6
7160.9
9685.2
14004.2
9404,5
98696
158380
15252.0
154794
148648
35.3
41.0
0.0
26
64.3
42.4
37.0
35.3
30.6
18.0
21.7
21.2
13,2
2.0
10.8
8,4
13.6
13.5
53.1
18.2
47.6
74.0
29.1
366
77.3
13.1
4.9
16.9
204
13.7
17.8
124
17.0
24.9
29.8
20.9
23.6
49.6
465
46
203
12.1
7.1
12.0
10.5
10.7
8.7
485
424
26.0
27.0
9.1
3.4
21.7
17,4
54.0
6.0
6.0
18,8
24.1
10.5
8.0
19.6
29.2
255
8.9
9.8
11.2
148
34p4
35.7
5.5
43
20.2
17.4
9.7
43.1
382
12.1
13.2
37.2
31.0
53.2
50.5
38.4
47.4
52.9
549
13.7
170
7.3
24.8
26.1
3.4
71
193
191
8.4
8.2
8.4
60
1766.3
2050.3
0.0
128.3
3213.7
2119.9
1852.4
1763.5
1530.8
902.4
1085.6
1061.8
661.4
98.9
537.8
4223
6798
673.3
2654.9
908.8
2378.2
3699.3
1405.7
1827.6
38669
654.1
2464
8474
10224
68653
892.3
618.4
850,2
1246.8
1491.4
1044.4
1179.9
2479.0
23251
2309
1015.0
605.5
354.5
599.1
5268
535.9
434.2
24231
21217
1301.6
1351.3
456.2
172.2
1087.4
869.4
2598.9
3014
300.5
938.1
1205.6
525.8
400.3
978.4
1462.1
1277,1
447.1
492.0
561.6
741,1
1718.6
1785.5
274.8
2125
1011.4
868.5
487.4
2156.5
1911.9
606.5
658.7
1858.8
1551,9
2659.5
2523.9
1922.0
2370.0
2646.6
2742.8
682.5
8492
362.8
1239,5
1302.7
167.6
355.5
966.5
9573
421.4
412.2
419,6
2996
2631.7
3004.9
0.0
160.8
4030.0
2658.3
3262.0
2001.6
1345.6
793.2
954.2
933.3
581.4
87,0
4727
859.9
13840
612.1
2909.8
996.0
3158.3
4912.6
2169.0
2723.2
6682.0
602.4
227.0
13186
1889.3
1066.2
1388.4
1121,7
1542.2
2457.5
2939,6
1561.3
1764.0
2813,7
4094.5
2099
11125
550.4
322.3
983.2
864.4
972.2
7877
36104
240851
2565.6
2491.7
420.2
158.6
1972.6
1577.1
3384.4
277.6
273.1
1028,2
1511.
431.2
328.3
902.1
1675.6
1463.5
811.0
892.4
873,8
11532
3026.5
3144.3
2531
1957
11085
1351.3
443.0
2471.4
2191.1
1232.9
1194.9
2778.9
2320,1
3779.1
3586.4
2410.2
3367.7
3760.9
38976
628s6
782.1
329.8
1420.5
1492.9
154.4
3274
15039
1489.6
783.4
641.5
854,3
2759
Annual
Annual CO,produced
Appliance/Light,
Electric Consumption from Appliance Electric
Consumption(Ib)
(kWhr)
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
79890
79890
78890
7989.0
7989.0
7989.0
7989.0
7989.0
79890
79890
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989,0
7989.0
7989.0
79890
789.0
79890
7989,0
7989.0
7989.0
79890
7989.0
7989.0
7989.0
7989.0
7989.0
789.0
7989.0
79890
7989.0
7989.0
79890
7989.0
789.0
7989.0
79890
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7889.0
7989.0
7989,0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989,0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
7989.0
79890
7989.0
789.0
789.0
79890
79890
11903.6
11903.6
10042-2
100182
10018.2
10018.2
14068.6
9067.5
7022.3
7022.3
7022.3
702Z3
7022.3
7022.3
7022.3
16265.6
16265.6
7262.0
8755.9
8755.9
10609.4
10609.4
11903.6
11903.6
138050
7357.9
7357.9
12430.9
14731.7
124309
12430,9
14492.0
14492.0
15746.3
15746.3
11943.5
11943.6
9067.5
14068,6
72620
8755.9
7262.0
7262.0
13109.9
13109.9
14492.0
14492.0
119036
90675
157463
14731.7
7357.9
7357.9
14492.0
14492,0
10018.2
7357.9
7262.0
8755,9
10018.2
6551.0
655190
7365.9
9155,4
9155.4
14492.0
14492.0
12430.9
12430.9
14068.6
14068.6
7357.9
7357.9
87559
124308
7262.0
9155.4
9159.4
16265.6
144920
11943.6
11943.6
11352.4
11352.4
10018.2
11352.4
11352.4
11352.4
7357.9
7357.9
7262.0
9155.4
9155.4
7357.9
7357.9
12430.9
12430.9
14851.6
12430.9
16265.6
73579
Net Electric
Consumption
C0 Produced from
(Appliance- MCRHP electricity fromgrid
producton) (kWhr) (grid average) (Ibs)
5690,5
6155.2
-829.3
2071.4
6734.7
6573.0
52928
5278.3
5847.3
6691,0
6982.8
5691.3
6771.0
5530.5
6127.7
2757.5
3539.9
3575.4
3944.0
3996.5
6916.5
7822.5
5487.6
5930,5
7880
32748
1550.1
3037.2
3497,0
2970.9
3481.7
19962
2566.0
3751.6
4116.9
4123.4
4340.8
6805.0
62376
1929.1
4167.0
3446.1
2454.4
2801.2
2492.4
1394.9
1339.9
67355
6130.1
3817.9
4150.1
2117.4
1579.2
3130.1
2654.1
5886.9
3122.0
1883.9
3920.5
4520.2
2422.1
2390.6
4070.8
5388.2
5149.0
741.1
509.9
3015.3
33806
50027
5014.8
4116.1
4067.6
4057.1
3723.3
3162,4
6450.2
5889.3
2069.7
1654.3
5380.9
5001.9
6585.2
8138.2
5824.6
663.9
6830.0
67201
3215.0
3153.5
1623.6
4805.5
5164.3
4168.6
2465.0
4279,4
40959
1741.6
1972.8
1683.0
21255
8478.8
9171.2
-1042.4
2597.5
8445.3
8242.6
9320.7
5990.9
5139.8
5881.4
6137.9
5082.6
5901.7
4861.3
5386.3
5614.3
7207.2
3250.1
4322.6
43502
9185.1
103883
8176.6
8836.5
138000
3016.1
1427.6
4725.8
6448.5
4622.7
54175
3821.1
4654.7
7394.4
8114.4
6164.5
64895
7723.7
10984.5
1753.6
4567.1
3132,5
2231.1
4596.7
4090.1
2530.3
2430.6
1030.9
6957.7
7525.0
7652.7
1950.2
14544
5678.0
4814.5
7382.1
2875.4
1712.4
42969
56683
1986.1
19603
3753.3
6174.9
5900.7
1344.3
925.0
4691.9
52603
88098
88311
3790.9
3746.3
4446.6
5793.5
2874.6
7391.9
6749.1
4214.0
3901.0
8044.5
7477.8
9357.5
8722.4
7304.1
8616.8
9705.5
9549.3
2961.0
29044
1475.9
5507.1
5918.3
3839.3
2270.2
6658.7
6373.2
3237.7
3069.6
3833.9
19576
CO. Produced from
annual electric
consumption (FF
emission rate) (lbs)
Total Annual C02
Total AnnualC02 lbs
Production(with
Production(1th FFemission
gridaverage
rates) (Ib.)
emission rates) (Ibs)
7423.
8329,5
-2612.0
-296.2
7831.9
7550.2
9045.7
4616.5
3944.7
5157.1
5576.4
3720.5
5272.1
3489.4
4347,7
4956.1
6646.6
946.2
1932.0
2020.6
9067.5
10368.5
7028.4
7891.6
138000
-2221.4
-6726.0
2378.6
5222.2
2244.1
3281.0
409.0
1747.9
5813.9
6670.1
3725.2
4187.5
7123.4
10805.8
-1407
2308.3
7611
-6579
3953.4
3408.5
-1004.1
-1133.2
9460.5
8015.3
5969,2
6604.7
-4573.2
-5666.9
3073,6
1955.0
6354.2
.2531.8
-1474.5
13554
3972.1
-3436.0
-3492.6
238.7
4180.1
3722.4
-2540.6
-30838
23343
3075.9
8505.2
85277
-5119
-610.4
2122.8
3771.6
355.2
6211.6
5138.7
3468.2
-394.4
398.8
5593.0
9003.7
8256.0
6245,7
6131.6
9413.4
9229.5
-2343.0
-24678
-1846.9
3065.4
3751.8
-405.1
-3867.0
4900.3
4527.9
801.2
217 9
38583
-5319.0
15882.6
16033,4
19743.5
14866
15041.
13798,2
19142.9
13490.1
10719.8
92409
9081,5
10478.8
8941.2
9809.1
95390
190775
19309.7
12747.3
150965
13138.2
14934.7
15703,2
15538,8
15833,4
284870
10332.2
10824.5
16250.8
18495.3
16032.0
16096.1
16723.3
17038.2
19013.7
19426.0
150865
15200.2
12938.7
19340.3
141628
13110.0
12828.4
13695.2
11088.5
18207.5
16685.0
165108
16248.8
131359
19109.4
18828.7
10732.3
10741,5
17364.2
17056.8
150678
10084.2
14276.1
12697.7
142778
11108.0
11028.5
11073.9
12449,0
12385.8
16644.9
16769.1
15817.1
15912.0
19102.3
19212.0
95596
9526.6
13199.2
15937.0
13034.2
12584.1
12692.8
19707.2
16859.7
15789.5
15485.8
16341.8
16534,4
14142.9
16379.8
16112.4
16343.9
1038&5
100729
14620.0
12556.4
12405.6
9434.4
10464.6
158086
15887.1
174226
16111.4
201920
98217
16937.6
16875.1
21313.2
17760.4
15655.2
14490.6
19417.9
14864.5
11914.9
9965.1
9643.0
11761,0
9620,8
11181.0
10577.6
197367
19870.3
150512
17487.1
15497,7
15062.3
15723.0
16686,9
16778.2
204670
15569.7
17978.2
18598.0
19721.6
18410.6
18232.6
19935.4
19945,0
205943
20870.3
17525.7
17502.2
13539.0
195189
17326.1
15368.8
15199.8
16584.2
187318
18889.1
20219.5
20074.7
168241
14078.3
20665.2
198767
17255.6
17862,9
19968.6
199163
16095.7
154914
17463.0
156392
15974.0
16530.2
16481.3
145885
14443.8
14564.1
20529.8
20777,9
181746
180963
19406.9
19515.3
13862.4
13883.3
15523.0
17958.9
1553.7
13764.4
14263.2
20453.0
20255.1
17435.2
17370.6
16695
17000.8
15201.2
16865.0
164045
16663.6
15692.4
159451
17942.8
14998.2
14572.1
136789
16601.8
175670
177324
198591
18931
20167.5
1709431
S.
Se
o"
0,
0:
Ee
E?
a 80P~
rr8
Ef
EY.
s
06
2Y
I CC
C
v
-
qM
I
1
0N M
-
C
C
Nl
V v
vIN
CC
C2
C,
-2.cC=-C
CC
N
CCCCC
C
C
C
22
NCC NC
I
l
I
CCCC
NN
I
I
-
v . I I m I I NI
V-2
-N.-
I
0 0
z
1
2CC
CC
0
CC
C
N
1 N VNI
N
_R.V,
9
N
N---
Q
;8N
N
''
o
.
---
ii
C
7
l
C
- .R
o __o
. 101 1
OD
4;NN
NN
q
N
C
-
1
1
-N
~
1
C
C
00C
..
N
V 1 0 q I M IQ
I
- -CC
-. -C-
aca0SI.I'N
N-
~
CCC
C
C0 CC
M
EC
C
CC
v
-.
-
-
CCP~N
C
C
C
orNR8RNo
N I:B~i
1 0 1 .
NNi"~ir~x~~
c
CC
q 9 0 -
C
~l
CON
0
C CCC CC CC
C
iia~s~-f
:5
C2
>CC)
CCCCCCCCC
CCC
CCo0
,
C
xCC
< > =.G
-
2
o
V
NN~~as~
CCCCCC-CC5C
CCC
CCC
CCC
CCC
C
C C C C
ec~m~s
C
C CC CCCC C
I C CC
NN
NN
-C
C
C C CCC 0 C CC
CCC
C
C
.C 0 C
~~~rmnom~m~a
on
, 0
C
z
3: Elau'o, . 2 2
QMz
CC
0 CC
CCC~a
-
N
C
C
CCCCCC
CCC
CCC
CCC
CCCCC
55555
C
CC
VT
CC 1
C------C
182lQPM
N"-14
C
Nq
R6$$
N
CC N CCC
CCC
CCCCCC
C
a~~~CCC
2
z
~ ~
<
CCC
CC
CCC
CCNCCCCCCC.CCC.C5CCC
CCCCCCCSSSC:Z.2CCCCCC
~"""
C
_,,,!
0
-NN
C
Cl
C C?
CCC CC
1
C C CC
N
2C
CC CC CCC CC
~
IF V- CClC
CCC
CCC
CCCCC
'~
C
C5CCC
%C
C
1,v '06 ccwo 'Qg 3
An
IC
-
CC
MC C C C
IINI;
C
C5UC
3
0, z
CCCCCCCCCC
C2CCCC q,,
~
CCCCCCCC~
N
I N0
9522"V
CC
CC
1 CC
M
NNN
C<Y
C CC
C2
C
0 CC
CCCCCC
NI
~
~CCC
CC
ZC4
-. 3i-C
'mi'-
C>
I
C
CMCCCCNC
C C C C C C C C C CO
CCC C
N
j . 1 0
2222s
CC CCC CC C
.O
NC C
C
-
0 1 1 RN 0 % .
C-CC
C
-N*MMNaeI.
NN
m.-.1
Vm.-NN.
-
N
o
C CC C
:c
I
C
0 C~~~
0-CCC
0 NI
CCC
C CC
5C.~CCCC
CCCC5CCC
C CCCCCC.2000S2C
CCC
CCC
CCC
CCC 22CCCC
CCC
CCC
CCC
CCCCCCCCCCCCCCCCCCCCCCC
CsS"""e
C'"~
Cn~cca~mo~C
CCCCC
C
CC
st&ZL)Sj ugg,%
'
EC
~~no
~~n ~a-6s~
0
CCC
I-
I19S1'922CC
C
C-C-CC
- CCCC
N
4
CCC
CN
v N
V
0
0=
09 g
2oiIL
.0
00C
c0
--
00
0
03~
41l
I0
0 0
N
000
No
Mmm
00 0
0
0
~
000v MO009On0
E0
0
00
N0
07
.
u~n
0.16>
o
00
0
00
00
M
0
WO~vWWmW
00.000-0-0000000000000~~~~q~~~00
M0 a0Wr
0
mm
NON0-
00
0
c;
z
zi
*~
-O
a .'s
0 -
o
, >6
'i2
o
0
o
__.!
Z
0t
a000
00
000 00 -
00000
-000Zoo00
_
,
00 -6
0
g
>on~oao
z~,o z
00000o
-0
,N
~
00
0
ON
0000000m'
00.- MON ON,
-VON N
.0.000
:N
-l
. CI6
*-
<>
(LU)
cr~
020-('(r
0
0
0 0 0
<>
z
0.0o0..
~D~~~m~~
0
XF
0
0
ON
V,
00000
0m
0
-
v 0W0
0 000
-NNNNNM
00<
>
,9~3~3
Do.
>
00000P0.0000N000N0p0N000v.N0v0000v00.q0N00000N
0
000
00
0
00
0
00
..
0
onM
NNNM4NV'
0 Mv 0 00
C)0
Z
< mz 'uIr Fn
7io~o0
0 0 Zz
~,,,,,,,
00-00V0o0I0N0N0V 00MO
00N0W0M-V-00N00000!0Ow0..00w.0.0N0v0000.0w00000V
00N00M00.0.0.0000-00Mo-m
0
.0
0
00
0
00
0
00
0
-0
00
O~N1~N1NOO~mPNN~
oLU
00E
'
1
0
-X0
OUO0
00
o
0
020
o
<. <~
0
6
a-00
0-
L)
00rr0.0-0-
0
co~c
0N00
:4010o
I0
0.
_<i
&0000
<<0
.E
o
Appendix F: State Average Data
State
Alabama
Arizona
Arkansas
California
Colorado
Massachusetts
Florida
Georgia
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maryland
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Jersey
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvannia
South Carolina
South Dakota
Tennessee
Texas
Utah
Virginia
Washington
West Virginia
Wisconsin
Wyoming
New Mexico
Connecticut
Vermont
New Hampshire
Maine
Delaware
Rhode Island
Pennsylvania
Alaska
Hawaii
MCHP State Average
C02 Ibs annual
Production (with FF
emission rates)
15957.9737
14568.873
16316.49553
9687.196729
19193.63409
13261.81343
15318.92118
15686.05603
10578.36533
17373.03483
16064.05205
16880.75944
19219.88927
15143.33514
16139.46729
13110.01022
18147.99176
16597.90015
14692.33042
18969.04012
10736.90338
17210.51514
12575.99308
12697.69758
11070.12099
12417.40768
16707.00949
15864.52086
19157.14361
9543.109632
14568.10447
12618.44567
18283.45432
15637.63958
15975.87299
10480.69392
12481.03502
9949.527968
15847.84721
16766.98309
15006.84285
14277.79951
12747.27747
14620.04066
14276.07228
14162.81125
13138.17311
13034.22936
14568.10447
19743.50316
20486.99574
GSHP State Average C02 Ibs
annual production (with FF
emission rates)
19395.24811
18699.43237
19251.53332
10702.5135
28847.25351
15888.52617
16083.68845
19314.96864
20986.04651
25922.60999
24391.87083
30970.90152
28583.78066
22426.67024
18173.60279
17071.66854
24468.35457
33495.32908
17130.6196
27262.27502
22247.68591
29450.08574
18473.59539
18120.32558
17831.63095
16835.61635
35968.74497
24172.38048
22675.17783
16350.13613
20348.27018
16252.25621
32390.13542
21284.78862
17880.43811
19283.86602
17240.63182
18353.69072
22311.12486
29366.72121
26890.07561
18195.99649
14940.20932
18210.07777
17310.80022
17486.47443
17250.94883
15447.27597
20348.27018
26014.58638
21353.8468
MCHP State Average
C02 Ibs annual
production (grid
average)
GSHP State
Average C02 Ibs
annual production
(grid average)
16906.34266
15968.70611
17141.1626
10666.20033
19803.51312
15892.02678
15392.63993
16732.54491
16773.94571
19159.77592
18321.58256
19940.20054
20732.30707
17513.95021
16528.93443
15368.7991
18810.4248
20147.06843
15451.23386
20270.97071
17559.22508
19942.46066
15793.57104
15639.20775
15866.64413
14503.9554
20653.85096
18135.45941
19461.12783
13872.83262
16740.94491
14013.81671
20354.05949
17402.91528
16471.78694
15818.77006
14785.16392
15140.34683
17649.69597
19411.07243
18632.92712
15974.03998
15051.16633
17942.77069
17462.95682
17326.07049
15497.74534
15553.69911
16740.94491
21313.15526
20486.99574
17630.92698
16263.90759
17923.75745
9273.465597
28114.00289
12741.7434
15633.48715
17569.55375
13534.81363
23674.87287
21599.00987
27212.32001
26540.95933
19315.26586
17064.29257
14158.45384
23670.37027
29160.96323
15335.06462
25515.84634
14106.6492
26038.37966
14208.58776
14398.25418
12005.74126
13756.30086
31070.2298
21430.76997
22203.96582
11433.59638
17570.9539
13406.83367
29842.40565
18512.29642
16714.32853
12763.30367
13998.92905
12341.70355
20004.11296
26200.19558
22568.47215
15901.71104
12139.35346
14216.43971
13645.2005
13756.7923
14274.92758
12461.4524
17570.9539
24033.33928
21153.96163
Conventional State
Average C02 Ibs
annual production
18891.44944
18043.4636
19622.71415
11279.86637
27096.74454
17805.58031
15887.46593
18923.03434
18958.67994
24654.93226
23211.8011
27273.55271
26578.30686
21142.26692
17966.19569
17534.97973
24749.72231
28654.27612
16616.4253
25801.53503
19964.96576
26490.81967
17508.71765
17945.09765
17461.79604
16181.81603
30114.26464
23054.72218
23132.09363
15399.61355
20045.11848
15135.87977
28882.83402
20104.737
17863.93294
17701.12441
16637.98861
16970.77417
21552.8256
26653.51069
24381.62625
18488.11653
16727.30969
20360.1494
19781.50415
19627.42975
17760.5773
17386.68357
20045.11848
27730.82378
20486.99574
44